Multi-component low and high entropy metallic coatings synthesized by pulsed magnetron sputtering

This paper presents the findings of the synthesis of multicomponent (Al, W, Ni, Ti, Nb) alloy coatings from mosaic targets. For the study, a pulsed magnetron sputtering method was employed under different plasma generation conditions: modulation frequency (10 Hz and 1000 Hz), and power (600 W and 1000 W). The processes achieved two types of alloy coatings, high entropy and classical alloys. After the deposition processes, scanning electron microscopy, X-ray diffraction, and energy-dispersive X-ray spectroscopy techniques were employed to find the morphology, thickness, and chemical and phase compositions of the coatings. Nanohardness and its related parameters, namely H3.Er2, H.E, and 1.Er2H ratios, were measured. An annealing treatment was performed to estimate the stability range for the selected coatings. The results indicated the formation of as-deposited coatings exhibiting an amorphous structure as a single-phase solid solution. The process parameters had an influence on the resulting morphology-a dense and homogenous as well as a columnar morphology, was obtained. The study compared the properties of high-entropy alloy (HEA) coatings and classical alloy coatings concerning their structure and chemical and phase composition. It was found that the change of frequency modulation and the post-annealing process contributed to the increase in the hardness of the material in the case of HEA coatings

Prediction of steel nanohardness by using graph neural networks on surface polycrystallinity maps

Funding Information: This research was funded by the European Union Horizon 2020 research and innovation program under grant agreement no. 857470 and from the European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS program grant no. MAB PLUS/2018/8 . We wish to acknowledge fruitful discussions with Daniel Cieslinski. | openaire: EC/H2020/857470/EU//NOMATENNanoscale hardness in polycrystalline metals is strongly dependent on microstructural features that are believed to be influenced from polycrystallinity — namely, grain orientations and neighboring grain properties. We train a graph neural networks (GNN) model, with grain centers as graph nodes, to assess the predictability of micromechanical responses of nano-indented 310S steel surfaces, based on surface polycrystallinity, captured by electron backscatter diffraction maps. The grain size distribution ranges between 1–100 μm, with mean size at 18μm. The GNN model is trained on nanomechanical load-displacement curves to make predictions of nano-hardness, with sole input being the grain locations and orientations. We explore model performance and its dependence on various structural/topological grain-level descriptors (e.g. grain size and number of neighbors). Analogous GNN-based frameworks may be utilized for quick, inexpensive hardness estimates, for guidance to detailed nanoindentation experiments, akin to cartography tool developments in the world exploration era.Peer reviewe

Microstructure and phase investigation of FeCrAl-Y2O3 ODS steels with different Ti and V contents

<p><strong><span>Description of data:</span></strong><span> The data set consists of seven main folders. The data is divided into folders based on the technique used to obtain the data. </span></p> <p><strong><span><span>      1.<span>      </span></span></span></strong><strong><span>XRD</span></strong><span> </span></p> <p><span>The XRD folder consists of two subfolders: </span></p> <p><span><span>·<span>        </span></span></span><strong><span>XRD of powder</span></strong><span>: raw data from diffractometer, which were used to create Fig. 3.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>XRD of bulk samples</span></strong><span>: raw data from diffractometer, which were used to prepare Fig. 10.</span></p> <p><strong><span><span>      2.<span>      </span></span></span></strong><strong><span>SEM</span></strong></p> <p><span>The SEM folder consists of six subfolders:</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of powder:</span></strong><span> SEM images, which were used to create Fig. 1 showing powder morphology.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>EDS of powder:</span></strong><span> SEM images and EDS spectra (<em>p11.tif</em>, <em>p13.tif</em>, <em>p30.tif</em>, <em>p32.tif</em>), which were used to create Fig. 2, show the chemical homogeneity of the powder.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of bulk samples:</span></strong><span> SEM images of bulk samples that were used to create Fig. 4.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>EDS of bulk samples:</span></strong><span> it consists of two SEM images of the region of interest (i.e., ODS-1-Ti.tif and ODS-2-TiV) and two .docx files (i.e., <em>ODS-1-Ti.docx</em> and <em>ODS-2-TiV.docx</em>) with maps of distribution of chemical elements selected for the analysis. These data were used to create Fig. 5. </span></p> <p><span><span>·<span>        </span></span></span><strong><span>EBSD of bulk samples:</span></strong><span> This subfolder consists of several files. <em>ODS-1-Ti_EBSD_grain_leg_info.txt</em> and <em>ODS-2-TiV_EBSD_grain_leg_info.txt</em> files<em> </em>consist of data from the EBSD software, which enable us to create a histogram of grain size in Fig. 9c. <em>ODS-1-Ti_EBSD_info.txt</em>, <em>ODS-1-Ti_EBSD_leg.bmp,</em> and <em>ODS-2-TiV_EBSD_info.txt, ODS-2-TiV_EBSD_leg.bmp</em> files contain information about the acquisition parameters of EBSD maps. <em>ODS-1-Ti_EBSD_IPF.bmp</em> and <em>ODS-2-TiV_EBSD_IPF.bmp</em> files are EBSD maps, which were used to create Fig. 9a and Fig. 9b.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of indentation sites:</span></strong><span> SEM images of indentation sites which were used to create Fig. 11c and Fig. 11d. </span></p> <p><strong><span><span>      3.<span>      </span></span></span></strong><strong><span>TEM</span></strong></p> <p><span>The TEM folder consists of two subfolders:</span></p> <p><span><span>·<span>        </span></span></span><strong><span>TEM of bulk samples:</span></strong><span> TEM/STEM images and data about precipitates (<em>Histograms data.xlsx</em>), which were used to create Fig. 7. </span></p> <p><span><span>·<span>        </span></span></span><strong><span>STEM EDS of bulk samples:</span></strong><span> In each subfolder (ODS-1-Ti and ODS-2-TiV), there are maps of the distribution of elements in both studied samples. These data were used to create Fig. 8.</span></p> <p><strong><span><span>      4.<span>      </span></span></span></strong><strong><span>Density:</span></strong><span> the<strong> </strong>folder contains a file with data related to the density measurements, which were used to create Table 3. </span></p> <p><strong><span><span>     5.<span>      </span></span></span></strong><strong><span>XRF:</span></strong><span> the folder contains two files related to XRF composition measurements. In the <em>XRF-graphs.docx</em> file, two plots are shown that are used to create Fig. 6. In <em>XRF_data.opju, </em>the data from the XRF device is shown. </span></p> <p><strong><span><span>     6.<span>      </span></span></span></strong><strong><span>Hardness:</span></strong><span> the folder contains a file with raw data of hardness measurements. </span></p> <p><strong><span>Nanoindentation:</span></strong><span> the folder contains two files, i.e., Nanoindentation.xlsx and Nanoindentation.opju, which contain nanoindentation data used to create Fig. 11a and Fig. 11b.</span></p&gt

Microstructure and phase investigation of FeCrAl-Y2O3 ODS steels with different Ti and V contents

<p><strong><span>Description of data:</span></strong><span> The data set consists of seven main folders. The data is divided into folders based on the technique used to obtain the data. </span></p> <p><strong><span><span>      1.<span>      </span></span></span></strong><strong><span>XRD</span></strong><span> </span></p> <p><span>The XRD folder consists of two subfolders: </span></p> <p><span><span>·<span>        </span></span></span><strong><span>XRD of powder</span></strong><span>: raw data from diffractometer, which were used to create Fig. 3.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>XRD of bulk samples</span></strong><span>: raw data from diffractometer, which were used to prepare Fig. 10.</span></p> <p><strong><span><span>      2.<span>      </span></span></span></strong><strong><span>SEM</span></strong></p> <p><span>The SEM folder consists of six subfolders:</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of powder:</span></strong><span> SEM images, which were used to create Fig. 1 showing powder morphology.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>EDS of powder:</span></strong><span> SEM images and EDS spectra (<em>p11.tif</em>, <em>p13.tif</em>, <em>p30.tif</em>, <em>p32.tif</em>), which were used to create Fig. 2, show the chemical homogeneity of the powder.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of bulk samples:</span></strong><span> SEM images of bulk samples that were used to create Fig. 4.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>EDS of bulk samples:</span></strong><span> it consists of two SEM images of the region of interest (i.e., ODS-1-Ti.tif and ODS-2-TiV) and two .docx files (i.e., <em>ODS-1-Ti.docx</em> and <em>ODS-2-TiV.docx</em>) with maps of distribution of chemical elements selected for the analysis. These data were used to create Fig. 5. </span></p> <p><span><span>·<span>        </span></span></span><strong><span>EBSD of bulk samples:</span></strong><span> This subfolder consists of several files. <em>ODS-1-Ti_EBSD_grain_leg_info.txt</em> and <em>ODS-2-TiV_EBSD_grain_leg_info.txt</em> files<em> </em>consist of data from the EBSD software, which enable us to create a histogram of grain size in Fig. 9c. <em>ODS-1-Ti_EBSD_info.txt</em>, <em>ODS-1-Ti_EBSD_leg.bmp,</em> and <em>ODS-2-TiV_EBSD_info.txt, ODS-2-TiV_EBSD_leg.bmp</em> files contain information about the acquisition parameters of EBSD maps. <em>ODS-1-Ti_EBSD_IPF.bmp</em> and <em>ODS-2-TiV_EBSD_IPF.bmp</em> files are EBSD maps, which were used to create Fig. 9a and Fig. 9b.</span></p> <p><span><span>·<span>        </span></span></span><strong><span>SEM of indentation sites:</span></strong><span> SEM images of indentation sites which were used to create Fig. 11c and Fig. 11d. </span></p> <p><strong><span><span>      3.<span>      </span></span></span></strong><strong><span>TEM</span></strong></p> <p><span>The TEM folder consists of two subfolders:</span></p> <p><span><span>·<span>        </span></span></span><strong><span>TEM of bulk samples:</span></strong><span> TEM/STEM images and data about precipitates (<em>Histograms data.xlsx</em>), which were used to create Fig. 7. </span></p> <p><span><span>·<span>        </span></span></span><strong><span>STEM EDS of bulk samples:</span></strong><span> In each subfolder (ODS-1-Ti and ODS-2-TiV), there are maps of the distribution of elements in both studied samples. These data were used to create Fig. 8.</span></p> <p><strong><span><span>      4.<span>      </span></span></span></strong><strong><span>Density:</span></strong><span> the<strong> </strong>folder contains a file with data related to the density measurements, which were used to create Table 3. </span></p> <p><strong><span><span>     5.<span>      </span></span></span></strong><strong><span>XRF:</span></strong><span> the folder contains two files related to XRF composition measurements. In the <em>XRF-graphs.docx</em> file, two plots are shown that are used to create Fig. 6. In <em>XRF_data.opju, </em>the data from the XRF device is shown. </span></p> <p><strong><span><span>     6.<span>      </span></span></span></strong><strong><span>Hardness:</span></strong><span> the folder contains a file with raw data of hardness measurements. </span></p> <p><strong><span>Nanoindentation:</span></strong><span> the folder contains two files, i.e., Nanoindentation.xlsx and Nanoindentation.opju, which contain nanoindentation data used to create Fig. 11a and Fig. 11b.</span></p&gt